SYSTEM AND METHOD FOR PROCESSING RAW ACTIVITY ENERGY EXPENDITURE DATA

• US 20100114499A1
• Filed: 01/06/2010
• Published: 05/06/2010
• Est. Priority Date: 12/27/2007
• Status: Abandoned Application

• Current Assignee: Kersh Risk Management Inc.
• Original Assignee: Move2Health Holding BV
• Inventors: Damen, Erik Petrus Nicolaas
• Application Number:
  US12/683,210
• Publication Number:
  US 20100114499A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 2220/836 Sensors arranged on the body of the user
• CPC Class Codes: A63B 2230/75 calorie expenditure
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 69/0028 for running, jogging or speed-walking movable endless bands A63B22/02
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

According to one embodiment, a method is provided for calculating, by an activity monitor comprising one accelerometer, a raw activity energy expenditure data based on movement by a user. The method includes determining if the raw activity energy expenditure data is associated with a high intensity physical activity, wherein the high intensity physical activity causes the raw activity energy expenditure data to differ from an expected activity energy expenditure data. The method includes calculating a corrected activity energy expenditure data, if the raw activity energy expenditure data is associated with the high intensity physical activity, based on the raw activity energy expenditure data, wherein the corrected activity energy expenditure data is substantially identical to the expected activity energy expenditure data.

Claims

1-30. -30. (canceled)

31. A method, comprising:

calculating a raw activity energy expenditure data based on movement by a user;

determining if the raw activity energy expenditure data is associated with a high intensity physical activity, wherein the high intensity physical activity causes the raw activity energy expenditure data to differ from an expected activity energy expenditure data; and

if the raw activity energy expenditure data is associated with the high intensity physical activity, calculating a corrected activity energy expenditure data based on the raw activity energy expenditure data.

32. The method of claim 31, further comprising:

displaying the corrected activity energy expenditure.

33. The method of claim 31, further comprising:

determining a speed of the user based on the raw activity energy expenditure data if the raw activity energy expenditure data is not associated with the high intensity physical activity; and

displaying the speed of the user.

34. The method of claim 33, wherein the speed of the user is determined by an equation given as (raw activity energy expenditure [RawAEE] metabolic equivalent (MET)−

1)/0.49 kilometer/hours (km/h) if the speed of the user is based on the raw activity energy expenditure data, or by (corrected activity energy expenditure MET−

1)/0.95 km/h if the speed of the user is based on the corrected activity energy expenditure data.

35. The method of claim 31, wherein the raw activity energy expenditure data in METs is calculated by (c*|a|)+1, wherein c is a predetermined value stored in the activity monitor, wherein |a| is the absolute value of the acceleration determined by an activity monitor and based on signals generated by an accelerometer.

36. The method of claim 31, wherein the determining if the raw activity energy expenditure data is associated with the high intensity physical activity comprises determining if the raw activity energy expenditure data is greater than a predetermined threshold value.

37. The method of claim 31, wherein the corrected activity energy expenditure data in METs is calculated by (RawAEE MET−

T)*B+F, wherein RawAEE MET is the raw activity energy expenditure data, wherein T is a predetermined threshold value associated with the high intensity physical activity, wherein B is a predetermined gradient value, and wherein F is a predetermined offset value.

38. The method of claim 31, wherein the corrected activity energy expenditure data comprises energy expended by the user in directions other than a direction of movement measured by an accelerometer.

39. The method of claim 31, wherein a selected one of the corrected activity energy expenditure data and the raw activity energy expenditure data are communicated over a network.

40. The method of claim 31, wherein the expected activity energy expenditure data in METs is determined by (G*v)+1, wherein G is a predetermined gradient value of 0.95 h/km during the high intensity physical activity and 0.49 h/km for low intensity physical activity, wherein v is a velocity of the user, 1 is one MET.

41. An apparatus, comprising:

an accelerometer;

a display; and

a processor, wherein the accelerometer and the processor are configured to interact in order to;

calculate a raw activity energy expenditure data based on movement by a user;

determine if the raw activity energy expenditure data is associated with a high intensity physical activity, wherein the high intensity physical activity causes the raw activity energy expenditure data to differ from an expected activity energy expenditure data; and

if the raw activity energy expenditure data is associated with the high intensity physical activity, calculate a corrected activity energy expenditure data based on the raw activity energy expenditure data.

42. The apparatus of claim 41, wherein the display is configured to display the corrected activity energy expenditure.

43. The apparatus of claim 41, further comprising:

a speed element configured to;

determine a speed of the user based on the raw activity energy expenditure data if the raw activity energy expenditure data is not associated with the high intensity physical activity, or based on the corrected activity energy expenditure data if the raw activity energy expenditure data is associated with the high intensity physical activity.

44. The apparatus of claim 43, wherein the speed of the user is determined by an equation given as (RawAEE MET−

1)/0.49 km/h if the speed of the user is based on the raw activity energy expenditure data, or by (CorAEE MET−

1)/0.95 km/h if the speed of the user is based on the corrected activity energy expenditure data, wherein the RawAEE MET is the raw activity energy expenditure data in METs, wherein the CorAEE MET is the corrected activity energy expenditure data in METs, wherein 1 is one MET.

45. The apparatus of claim 41, wherein the raw activity energy expenditure data in METs is calculated by (c*|a|)+1, wherein c is a predetermined value stored in the activity monitor, wherein |a| is the absolute value of the acceleration determined by activity monitor based on signals generated by the one accelerometer, wherein 1 is one MET.

46. The apparatus of claim 41, wherein a selected one of the corrected activity energy expenditure data and the raw activity energy expenditure data are communicated over a network to a server.

47. The apparatus of claim 41, wherein the corrected activity energy expenditure data in METs is calculated by an equation given as (RawAEE_MET−

T)*B+F, wherein RawAEE_MET is the raw activity energy expenditure data, wherein T is a predetermined threshold value associated with the high intensity physical activity, wherein B is a predetermined gradient value, wherein F is a predetermined offset value.

48. The apparatus of claim 41, wherein the accelerometer is a piezo-electric accelerometer.

49. The apparatus of claim 41, wherein a selected one of the corrected activity energy expenditure data and the raw activity energy expenditure data are stored in a memory element and accessible through a web portal.

50. Logic encoded in computer-readable media to be executed by a processor configured to perform operations comprising:

calculating a raw activity energy expenditure data based on movement by a user, the movement measured by one accelerometer;

determining if the raw activity energy expenditure data is associated with a high intensity physical activity, wherein the high intensity physical activity causes the raw activity energy expenditure data to differ from an expected activity energy expenditure data;

calculating a corrected activity energy expenditure data, if the raw activity energy expenditure data is associated with the high intensity physical activity, based on the raw activity energy expenditure data, wherein the corrected activity energy expenditure is displayed;

determine a speed of the user based on the raw activity energy expenditure data if the raw activity energy expenditure data is not associated with the high intensity physical activity, or based on the corrected activity energy expenditure data if the raw activity energy expenditure data is associated with the high intensity physical activity; and

display the speed of the user, wherein the determining if the raw activity energy expenditure data is associated with the high intensity physical activity comprises determining if the raw activity energy expenditure data is greater than a predetermined threshold value.